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Analyzing Linguistic Data
A Practical Introduction to Statistics using R

$54.99 (X)

textbook
  • Date Published: March 2008
  • availability: In stock
  • format: Paperback
  • isbn: 9780521709187

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  • Statistical analysis is a useful skill for linguists and psycholinguists, allowing them to understand the quantitative structure of their data. This textbook provides a straightforward introduction to the statistical analysis of language. Designed for linguists with a non-mathematical background, it clearly introduces the basic principles and methods of statistical analysis, using 'R', the leading computational statistics programme. The reader is guided step-by-step through a range of real data sets, allowing them to analyse acoustic data, construct grammatical trees for a variety of languages, quantify register variation in corpus linguistics, and measure experimental data using state-of-the-art models. The visualization of data plays a key role, both in the initial stages of data exploration and later on when the reader is encouraged to criticize various models. Containing over 40 exercises with model answers, this book will be welcomed by all linguists wishing to learn more about working with and presenting quantitative data.

    • Assumes no mathematical or scientific knowledge, and no prior experience with using statistical methods and tools
    • Introduces the use of 'R', the prominent and leading computational statistics programme
    • Guides the reader step-by-step through various analyses of a range of language data sets, aided by over 40 exercises with model answers
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    Product details

    • Date Published: March 2008
    • format: Paperback
    • isbn: 9780521709187
    • length: 368 pages
    • dimensions: 247 x 174 x 21 mm
    • weight: 0.75kg
    • contains: 67 b/w illus. 4 tables 42 exercises
    • availability: In stock
  • Table of Contents

    1. An introduction to 'R'
    2. Graphic data exploration
    3. Probability distributions
    4. Basic statistical methods
    5. Clustering and classification
    6. Regression modeling
    7. Mixed models
    Appendix A. Solutions to the exercises
    Appendix B. Overview of 'R' functions.

  • Instructors have used or reviewed this title for the following courses

    • Advance Research Methods. Analyzing data with R
    • Advanced Laboratory Research
    • Analyzing Linguistic Data
    • Corpus Linguistics
    • Digital Humanities
    • Experimental Methods in Linguistics
    • Intro to Span Sociolinguistics
    • Introduction to Linguistic Analysis
    • Language and Computers
    • Methodologies
    • Multivariate Statistics
    • Quantitative Methods in Phonetics and Phonology
    • Research Design and Statistics
    • Statistics for Linguists
    • The Science of Linguistics
    • Topics in Computational Linguistics
  • Author

    R. H. Baayen, University of Alberta
    R. H. Baayen is Professor of Quantitative Linguistics at Radboud University of Nijmegen and the Max Planck Institute for Psycholinguistics, Nijmegen.

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